1、选择要安装的版本http://kafka.apache.org/downloads
2、wget https://mirrors.bfsu.edu.cn/apache/kafka/2.8.0/kafka_2.12-2.8.0.tgz
3、tar -xzvf kafka_2.12-2.8.0.tgz
4、重要的文件夹 bin（所用sh文件都在这里） 和 config（所有配置文件都在这里）
5、修改zookeeper.properties和server.properties（这里有个重要的概念 kafka是依赖于zookeeper的）
# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # the directory where the snapshot is stored. dataDir=/tmp/zookeeper # the port at which the clients will connect clientPort=2181 # disable the per-ip limit on the number of connections since this is a non-production config maxClientCnxns=0 # disable the adminserver by default to avoid port conflicts. # Set the port to something non-conflicting if choosing to enable this admin.enableServer=false # admin.serverPort=8080
Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # see kafka.server.KafkaConfig for additional details and defaults ############################# Server Basics ############################# # The id of the broker. This must be set to a unique integer for each broker. broker.id=0 ############################# Socket Server Settings ############################# host.name=192.168.232.128 # The address the socket server listens on. It will get the value returned from # java.net.InetAddress.getCanonicalHostName() if not configured. # FORMAT: # listeners = listener_name://host_name:port # EXAMPLE: # listeners = PLAINTEXT://your.host.name:9092 listeners=PLAINTEXT://:9092 # Hostname and port the broker will advertise to producers and consumers. If not set, # it uses the value for "listeners" if configured. Otherwise, it will use the value # returned from java.net.InetAddress.getCanonicalHostName(). advertised.listeners=PLAINTEXT://192.168.232.128:9092 # Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details #listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL # The number of threads that the server uses for receiving requests from the network and sending responses to the network num.network.threads=3 # The number of threads that the server uses for processing requests, which may include disk I/O num.io.threads=8 # The send buffer (SO_SNDBUF) used by the socket server socket.send.buffer.bytes=102400 # The receive buffer (SO_RCVBUF) used by the socket server socket.receive.buffer.bytes=102400 # The maximum size of a request that the socket server will accept (protection against OOM) socket.request.max.bytes=104857600 ############################# Log Basics ############################# # A comma separated list of directories under which to store log files log.dirs=/tmp/kafka-logs # The default number of log partitions per topic. More partitions allow greater # parallelism for consumption, but this will also result in more files across # the brokers. num.partitions=1 # The number of threads per data directory to be used for log recovery at startup and flushing at shutdown. # This value is recommended to be increased for installations with data dirs located in RAID array. num.recovery.threads.per.data.dir=1 ############################# Internal Topic Settings ############################# # The replication factor for the group Metadata internal topics "__consumer_offsets" and "__transaction_state" # For anything other than development testing, a value greater than 1 is recommended to ensure availability such as 3. offsets.topic.replication.factor=1 transaction.state.log.replication.factor=1 transaction.state.log.min.isr=1 ############################# Log Flush Policy ############################# # Messages are immediately written to the filesystem but by default we only fsync() to sync # the OS cache lazily. The following configurations control the flush of data to disk. # There are a few important Trade-offs here: # 1. Durability: Unflushed data may be lost if you are not using replication. # 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush. # 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks. # The settings below allow one to configure the flush policy to flush data after a period of time or # every N messages (or both). This can be done globally and overridden on a per-topic basis. # The number of messages to accept before forcing a flush of data to disk log.flush.interval.messages=10000 # The maximum amount of time a message can sit in a log before we force a flush log.flush.interval.ms=3000 ############################# Log Retention Policy ############################# # The following configurations control the disposal of log segments. The policy can # be set to delete segments after a period of time, or after a given size has accumulated. # A segment will be deleted whenever *either* of these criteria are met. Deletion always happens # from the end of the log. # The minimum age of a log file to be eligible for deletion due to age log.retention.hours=168 # A size-based retention policy for logs. Segments are pruned from the log unless the remaining # segments drop below log.retention.bytes. Functions independently of log.retention.hours. #log.retention.bytes=1073741824 # The maximum size of a log segment file. When this size is reached a new log segment will be created. log.segment.bytes=1073741824 # The interval at which log segments are checked to see if they can be deleted according # to the retention policies log.retention.check.interval.ms=300000 ############################# Zookeeper ############################# # Zookeeper connection string (see zookeeper docs for details). # This is a comma separated host:port pairs, each corresponding to a zk # server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002". # You can also append an optional chroot string to the urls to specify the # root directory for all kafka znodes. zookeeper.connect=localhost:2181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=18000 ############################# Group Coordinator Settings ############################# # The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance. # The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms. # The default value for this is 3 seconds. # We override this to 0 here as it makes for a better out-of-the-Box experience for development and testing. # However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup. group.initial.rebalance.delay.ms=0
192.168.232.128是我的虚拟机的ip
2181是zookeeper的端口 9092是kafka的端口
6、进入到解压的文件夹
7、启动zookeeper bin/zookeeper-server-start.sh config/zookeeper.properties
8、启动kafka bin/kafka-server-start.sh config/server.properties
9、创建topic bin/kafka-topics.sh --create --zookeeper 192.168.232.128:2181 --replication-factor 1 --partitions 1 --topic kafka-hello
10、开始测试
11、启动发布者进行消息写入 bin/kafka-console-producer.sh --broker-list 192.168.232.128:9092 --topic kafka-hello
12、启动订阅者进行消息读取 bin/kafka-console-consumer.sh --bootstrap-server 192.168.232.128:9092 --topic kafka-hello --from-beginning
13、一切顺利的话就算搭建完成
14、还差一步应该就完美了，设置一下开机启动
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.net core 连接 kafka
有百度到两个比较靠谱的插件Confluent.Kafka和kafka-net-core
参考自 kafka-net-core https://blog.csdn.net/zt102545/article/details/105268492/
生产者
const string topicName = "test";
var options = new KafkaOptions(new Uri("http://localhost:9092"));
//创建一个生产者发消息
using (var producer = new Producer(new brokerRouter(options)){ BatchSize = 100, BatchDelayTime = TimeSpan.FromMilliseconds(2000) })
{
while (true)
{
var message = Console.ReadLine();
if (message == "quit") break;
if (!string.IsNullOrEmpty(message))
{
producer.SendMessageAsync(topicName, new[] { new Message(message) });
}
}
}
消费者
const string topicName = "test";
var options = new KafkaOptions(new Uri("http://localhost:9092"));
Task.Run(() =>
{
//创建一个消费者
var consumer = new Consumer(new ConsumerOptions(topicName, new brokerRouter(options)));
foreach (var data in consumer.Consume())
{
Console.WriteLine("Response: PartitionId={0},Offset={1} :Value={2}", data.Meta.PartitionId, data.Meta.Offset, data.Value.ToUtf8String());
}
});
Console.ReadLine();
参考自 Confluent.Kafka https://www.cnblogs.com/meowv/p/13614516.html
发布
public async Task PublishAsync<TMessage>(string topicName, TMessage message) where TMessage : class
{
var config = new ProducerConfig
{
BootstrapServers = "192.168.232.128:9092"
};
using var producer = new ProducerBuilder<string, string>(config).Build();
var sss = await producer.ProduceAsync(topicName, new Message<string, string>
{
Key = Guid.NewGuid().ToString(),
Value = JsonConvert.SerializeObject(message)
});
}
public async Task SubscribeAsync<TMessage>(IEnumerable<string> topics, Action<TMessage> messageFunc, CancellationToken cancellationToken) where TMessage : class
{
var config = new ConsumerConfig
{
BootstrapServers = "127.0.0.1:9092",
GroupId = "crow-consumer",
EnableAutoCommit = false,
StatisticsIntervalMs = 5000,
SessionTimeoutMs = 6000,
AutoOffsetReset = AutoOffsetReset.Earliest,
EnablePartitionEof = true
};
//const int commitPeriod = 5;
using var consumer = new ConsumerBuilder<Ignore, string>(config)
.SetErrorHandler((_, e) =>
{
Console.WriteLine($"Error: {e.Reason}");
})
.SetStatisticsHandler((_, json) =>
{
Console.WriteLine($" - {DateTime.Now:yyyy-MM-dd HH:mm:ss} > 消息监听中..");
})
.SetPartitionsAssignedHandler((c, partitions) =>
{
string partitionsstr = string.Join(", ", partitions);
Console.WriteLine($" - 分配的 kafka 分区: {partitionsstr}");
})
.SetPartitionsRevokedHandler((c, partitions) =>
{
string partitionsstr = string.Join(", ", partitions);
Console.WriteLine($" - 回收了 kafka 的分区: {partitionsstr}");
})
.Build();
consumer.Subscribe(topics);
try
{
while (true)
{
try
{
var consumeResult = consumer.Consume(cancellationToken);
Console.WriteLine($"Consumed message '{consumeResult.Message?.Value}' at: '{consumeResult?.TopicPartitionOffset}'.");
if (consumeResult.IsPartitionEOF)
{
Console.WriteLine($" - {DateTime.Now:yyyy-MM-dd HH:mm:ss} 已经到底了：{consumeResult.Topic}, partition {consumeResult.Partition}, offset {consumeResult.Offset}.");
continue;
}
TMessage messageResult = null;
try
{
messageResult = JsonConvert.DeserializeObject<TMessage>(consumeResult.Message.Value);
}
catch (Exception ex)
{
var errorMessage = $" - {DateTime.Now:yyyy-MM-dd HH:mm:ss}【Exception 消息反序列化失败，Value：{consumeResult.Message.Value}】 ：{ex.StackTrace?.ToString()}";
Console.WriteLine(errorMessage);
messageResult = null;
}
if (messageResult != null/* && consumeResult.Offset % commitPeriod == 0*/)
{
messageFunc(messageResult);
try
{
consumer.Commit(consumeResult);
}
catch (KafkaException e)
{
Console.WriteLine(e.Message);
}
}
}
catch (ConsumeException e)
{
Console.WriteLine($"Consume error: {e.Error.Reason}");
}
}
}
catch (OperationCanceledException)
{
Console.WriteLine("Closing consumer.");
consumer.Close();
}
await Task.CompletedTask;
}
都亲测有效
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